Interlace motion artifact detection using vertical frequency detection and analysis

ABSTRACT

An interlace motion artifact detector which identifies video image spatial frequencies characteristic of motion artifacts. The detected frequency is the maximum which can be represented by the vertical sampling rate of the video format (i.e., the Nyquist frequency). This frequency is detected by a pair of partial Discrete Fourier Transforms (DFT) which each calculate only the frequency component of interest. Additional vertical frequency components at one half and one quarter the interlace motion artifact frequency are also detected via a partial DFT. The presence of these lower frequencies acts as an indication of an erroneous motion artifact detection. Additionally, the dynamic range and maximum level of the video data is used as an indication of when to boost the frequency detection levels in areas of low brightness and/or contrast.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a divisional of U.S. application Ser. No.11/054,748 filed Feb. 9, 2005, now U.S. Pat. No. 7,391,481 which is adivisional of U.S. application Ser. No. 09/941,949 filed Aug. 28, 2001entitled “Interlace Motion Artifact Detection Using Vertical FrequencyDetection and Analysis” (now U.S. Pat. No. 6,909,469 issued Jun. 21,2005) which is a continuation-in-part of U.S. patent application Ser.No. 09/372,713 filed Aug. 11, 1999 entitled “Method and Apparatus forDetection Frequency In Digital Video Images,” (now U.S. Pat. No.6,489,998 issued Dec. 3, 2002), which are incorporated herein byreference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to the processing of videoimages, and more particularly to techniques for deinterlacing videoimages.

2. Description of the Related Art

The world's major television standards use a raster scanning techniqueknown as “interlacing.” Interlaced scanning draws horizontal scan linesfrom the top of the screen to the bottom of the screen in two separatepasses, one for even numbered scan lines and the other for odd numberedscan lines. Each of these passes is known as a field.

It is often necessary and/or desirable to convert an interlaced videosignal to a progressively scanned signal. A single image or frame of aprogressively scanned video source is scanned from the top of the screento the bottom in a single pass. Such a conversion is advantageous, forexample, when using a progressive scan display. Many of the displaydevices used to show interlaced video signals are actually progressivein nature. Common examples of such progressive displays are computerCRTs and liquid crystal displays (LCDs). One advantage of such displaysis that they eliminate many of the deficiencies of interlaced videoformats, such as flicker, line twitter, and visible scan line structure.Another advantage of the progressive scan format is improvement in thecompression ratio of a digital format, such as a digital broadcast orsatellite transmission.

In order for such an interlaced video image to be utilized by aprogressively scanned video system, it must be converted from aninterlaced scan format to a progressive scan format. There are a numberof standard techniques for performing this conversion, and range fromsimple merging of adjacent fields, to interpolation from a single fieldto form a progressive frame, to more complex motion-adaptive techniques.

Motion-adaptive deinterlacing of interlaced video sequences is a methodwhich optimizes image quality by utilizing different deinterlacingtechniques in image areas with and without motion. Where there is nomotion in an image, pixel data from adjacent interlaced fields cansimply be merged to form a progressive frame since the two fields areeffectively temporally consistent. However, where motion exists in theimage, two adjacent fields cannot simply be combined without generatinginterlace motion artifacts since the fields are not temporallyconsistent in those areas (with motion). Instead, new pixels must becalculated based on the temporally ‘current’ field so that the entireoutput image is temporally consistent. Motion-adaptive deinterlacingmerges these two approaches by combining data from two fields at imagelocations where there is no motion, and calculating new pixel data atimage locations where there is motion. To do this, motion in the imagemust be detected on a pixel by pixel basis in order to decide whichdeinterlacing technique to apply at each pixel location.

Prior art in this field makes use of a number of techniques to detectimage motion. A generally used method is to compute the differencebetween two fields. A significant difference is classified as ‘motion’.One such method is to calculate the difference between spatially similarpixels in pairs of even fields and pairs of odd fields. (I.e., fieldpairs which are two field periods apart.) Another method calculates thedifference between one field and a spatially coincident ‘virtual’ fieldwhich is created from a temporally adjacent but spatially non-coincidentfield. (I.e., the fields are one field period apart.)

The specific artifacts created by combining two fields with motion mayalso be detected. U.S. Pat. No. 5,625,421 discloses such a method, whichdetects “sawtooth” artifacts by testing sets of three verticallyadjacent pixels for characteristics indicative of motion artifacts. Yetanother method, disclosed in U.S. patent application Ser. No.09/372,713, identifies motion artifacts by utilizing Fourier analysis todetect the presence of a specific vertical frequency which ischaracteristic of interlace motion artifacts. This prior artimplementation of the identification of interlace motion artifactslooked only for a single frequency component. This frequency componentis the maximum frequency (f_(max)) which can be represented by thevertical sampling rate of the video format—i.e., half the Nyquistsampling rate. The f_(max) frequency was identified by performing apartial Discrete Fourier Transform (DFT) which calculated only thespecific frequency component of interest in local area around a givenpixel location. Essentially, this partial DFT multiplied a verticalarray of pixel values by the amplitude of a cosine wave of the f_(max)frequency, and then summed the results of the individualmultiplications. The absolute value of this sum was used as theamplitude of the f_(max) frequency component.

While the latter frequency-based method does detect interlace motionartifacts, it also has a potential shortcoming in that it alsoerroneously detects high frequencies in certain static image features as‘motion’. An example of this is illustrated in FIG. 1, which shows asimple example image 10 composed of a single rectangle 12 which has adifferent luminosity than the image background 14. The horizontallyaligned borders 16 of the rectangle, when scanned in the verticaldirection, appear as sharp transitions also known as a step function. Anexample of a step function is shown in FIG. 2, which also shows thefrequency composition of such a step function. Although the stepfunction is largely composed of lower frequencies 20, the specificfrequency 22 which is characteristic of interlace motion artifacts isalso present. Because this frequency is present in such images, it maybe detected as a possible artifact, resulting in inaccurate detection.What is needed is a more accurate and reliable method of frequencydetection which identifies interlace motion artifacts but rejects staticimage features which are not motion artifacts.

SUMMARY OF THE INVENTION

The present invention meets these needs by providing an accurate methodand apparatus for reliably detecting interlace motion artifacts. Itshould be appreciated that the present invention and various discretefeatures thereof can be implemented in numerous ways, including as aprocess, an apparatus, a system, a device, or a method. Furthermore,various discrete apparatus of the invention can be implemented insoftware or hardware. Several inventive embodiments of the presentinvention are described below.

In one embodiment of the present invention, a method for detectinginterlace motion artifacts is disclosed. The method includes detectingthe presence of multiple vertical frequencies in an image, and analyzingthe relative levels of those frequencies to derive an indication of thepresence of motion artifacts. In addition, the overall image intensityis taken into account in the detection, with the indication of interlacemotion artifacts being boosted in areas of low luminosity or chromalevel.

In another embodiment of the present invention, a method for thedetection of interlaced motion artifacts includes obtaining eightvertically aligned luma data samples, calculating a partial discretefourier transform for a f_(max) value, calculating a partial discretefourier transform for a f_(max)/2 value and calculating a partialdiscrete fourier transform for a f_(max)/4 value.

In yet another embodiment of the present invention, a method forboosting frequency detection values in areas of low brightness andcontrast is disclosed. The method includes obtaining a plurality ofinput pixel data values, determining a maximum value, determining arange value and selectively boosting a frequency detection value basedupon the maximum value, the range value and a plurality of filteredfrequency detection values.

In another embodiment of the present invention, a method for theprevention of false detection of interlace motion artifacts includesobtaining a plurality of f_(max) frequency detection values, comparingthe plurality of f_(max) frequency detection values to a threshold andadjusting the plurality of f_(max) frequency detection values based uponthe comparison.

In another embodiment of the present invention, a system for thereduction of interlace motion artifacts by vertical frequency analysisis disclosed. The system includes a four-point partial discrete fouriertransform module responsive to a set of four vertically aligned lumadata sample inputs selected from and approximately centered about a setof eight vertically aligned luma data sample inputs and operative todevelop a first frequency detection value. Also included is aneight-point partial discrete fourier transform module responsive to theset of eight vertically aligned luma data sample inputs and operative todevelop a second, third and fourth frequency detection value. A dynamicrange/maximum detection module responsive to the set of eight verticallyaligned luma data sample inputs in conjunction with pixel data from atwo-dimensional array surrounding a current input pixel and operative todevelop a maximum data value and a range value. The horizontal lowpassfilter module is responsive to the first, second, third and fourthfrequency detection values and operative to develop filtered first,second, third and fourth frequency detection values. The detection valueboost module is responsive to the filtered first, second, third andfourth frequency detection values, the maximum data value and the rangevalue, and is operative to develop a level boosted four-point f_(max)frequency detection value, a level boosted eight-point f_(max) frequencydetection value, a level boosted f_(max)/2 frequency detection value anda level boosted f_(max)/4 frequency detection value. An averaging moduleis responsive to the level boosted four-point frequency detection valueand the level boosted eight-point frequency detection value, and isoperative to develop a numeric average. A threshold comparison/levelcorrection module is responsive to the numeric average, the levelboosted f_(max)/2 frequency detection value and the level boostedf_(max)/4 frequency detection value, and is operative to develop alevel-corrected f_(max) frequency detection value. The horizontalweighted average module is responsive to the level-corrected f_(max)frequency detection value and operative to develop a center-weightedhorizontal frequency detection value. Finally, a threshold adjust moduleis responsive to the center-weighted horizontal frequency detectionvalue and operative to develop a final frequency detection value.

The present invention advantageously allows for the reduction ofartifacts in deinterlaced video images. By correctly and accuratelyidentifying interlace motion artifacts, a video deinterlacer can combinepixels from two fields in areas which do not have motion artifacts andto process the image to remove motion artifacts in areas where suchartifacts are present. The result is a progressive video image which isfree of defects and motion artifacts. Further, the deinterlacingpreserves the maximum amount of vertical detail in the image.

Other aspects and advantages of the invention will become apparent fromthe following detailed description, taken in conjunction with theaccompanying drawings, illustrating by way of example the principles ofthe invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will be readily understood by the followingdetailed description in conjunction with the accompanying drawingswherein:

FIG. 1 illustrates an image which causes problems with a prior artmethod of identifying interlace motion artifacts via vertical frequencydetection;

FIG. 2 illustrates time domain and frequency domain plots of the stepfunction found at the vertical boundaries of certain image features;

FIG. 3 illustrates a high level block diagram depicting the signalprocessing data path of the interlace motion artifact frequency detectorof the present invention;

FIG. 4 is an illustration used to describe the method of thresholding afrequency detection value of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

A method and apparatus for accurate detection of interlace motionartifacts by vertical frequency analysis is disclosed. In the followingdescription, numerous specific details are set forth in order to providea thorough understanding of the present invention. It will be understoodhowever that the present invention may be practiced without some or allof these specific details. In other instances, well known processoperations have not been described in detail in order not tounnecessarily obscure the present invention.

In a preferred embodiment of the invention, at each pixel location forwhich a detection of interlaced motion artifacts is needed, calculationsfor the detection of two specific lower frequencies are performed, alongwith two calculations for f_(max) over two varying sample set sizes. Asignal flow block diagram of the invention is shown in FIG. 3. Eightvertically aligned luma data samples 30 from a frame formed from themerging of two adjacent fields are the input to the frequency detector.The eight data samples are roughly centered around the pixel locationfor which the motion artifact detection is being performed (Row N inFIG. 3). Three eight-point partial DFT calculations 32 are performed,resulting in frequency amplitude level values 34, 36 and 38 for f_(max),f_(max)/2, and f_(max)/4, respectively.

The three frequency detection calculations 32 are performed as follows.For a given frequency to be detected, the eight data sample values areeach multiplied by the value of a complex sinusoid, or basis function,of the appropriate frequency. The basis function's value at a givenpixel location is multiplied by that pixel's value. The resulting valuesare then summed to form a complex result for that frequency component.This process is essentially the calculation of a DFT for the singlefrequency. The magnitude of the sum is calculated and it represents theamplitude of the frequency at the given pixel location. The general formof the frequency calculation is:

$\begin{matrix}{F_{k} = {\sum\limits_{n = 0}^{7}{P_{n}{\mathbb{e}}^{{- {j2\pi}}\;{{kn}/8}}}}} & {{Equation}\mspace{20mu} 1}\end{matrix}$where ‘Fk’ is the kth frequency component, ‘n’ is the pixel samplenumber, and ‘Pn’ is the value of the nth pixel. The complex exponentialis the basis function for the kth frequency component, and is composedof a real cosine component and an imaginary sine component.

For example, the f_(max) frequency component has the following basisfunction values for the eight data sample locations as set forth inTable one:

TABLE ONE cosine: [1, −1, 1, −1, 1, −1, 1, −1] sine: [0,   0, 0,   0, 0,  0, 0,   0]Note that the pixel data value for Row N−3 in FIG. 3 is assumed to bealigned with n=0. Since the value of the sine component is zero for alleight locations, only the cosine values need to be considered and theresulting frequency component value has no imaginary component. Themagnitude calculation is therefore simplified to summing the eightmultiplication results and taking the absolute value.

For the half and quarter f_(max) frequency components, the basisfunction values are, respectively, as in Table Two:

TABLE TWO cosine: [1. 0, −1,   0, 1, 0, −1,   0] sine: [0, 1,   0, −1,0, 1,   0, −1] cosine: [1, 0.7071, 0, −0.7071, −1, −0.7071,   0,  0.7071] sine: [0, 0.7071, 1,   0.7071,   0, −0.7071, −1, −0.7071]Since the sine component is not zero for these two basis functions, theresultant frequency value will have an imaginary component. Themagnitude calculation is then the traditional square root of the sum ofthe squares of the summed real and imaginary multiplications. Forreduction of computational complexity and/or hardware implementation, anestimate of the magnitude may be calculated by taking the sum of theabsolute values of the real and imaginary components. For similarreasons, the f_(max)/4 calculations may choose to use an approximationto the value of squareroot(2)/2 (i.e, 0.7071).

A second f_(max) calculation 40 is performed which is based on fourpixel data values, yielding a secondary f_(max) frequency magnitude 42.The four-point frequency calculation is performed because empiricaltesting results have demonstrated that a combination of the four-pointand eight-point f_(max) detections yield more consistent results over awide variety of source material. The frequency detection values 34, 36,38 and 42 are then passed through a horizontal lowpass filter 44,producing filtered versions 46 of the input frequency detection values.This filtering process smooths out irregularities in the response of thepixel-by-pixel frequency detection values caused by noise and otherproblems. In the preferred embodiment, the lowpass filter is implementedas a simple averaging operation as follows:FilterOut=(F _(n−2)+2*F _(n−1)+2*F _(n)+2*F _(n+1) F _(n+2))/8  EquationThreewhere F_(n) is the current input frequency detection value to thefilter, F_(n−1) is the previous input frequency detection value, etc.

It will therefore be appreciated that a method for detecting interlacemotion artifacts includes obtaining eight vertically aligned luma datasamples, calculating a partial discrete fourier transform for a f_(max)value, calculating a partial discrete fourier transform for a f_(max)/2value and calculating a partial discrete fourier transform for af_(max)/4 value. The method also includes obtaining four verticallyaligned luma data samples, calculating a second f_(max) value andpassing the f_(max) value, the f_(max)/2 value, the f_(max)/4 value andthe second f_(max) value though a filter resulting in a filtered f_(max)value, a filtered f_(max)/2 value, a filtered f_(max)/4 value and afiltered second f_(max) value. The filtered values are obtained byobtaining a first and second previous f_(max) values, a current f_(max)value and a next and second next f_(max) values, doubling the firstprevious, current and next f_(max) values, summing the doubled firstprevious, current and next f_(max) values with the second previous andsecond next f_(max) value and dividing the sum by 8.

The calculated frequency detection values are proportional to the rangeof the data from which they were calculated. Because of this, thefrequency detection values will be relatively low in areas of lowoverall brightness and low contrast, and need to be boosted in theseareas. To accomplish this, the eight input pixel data values 30 are alsofed to a module 50 which determines the maximum data value and the rangefrom maximum to minimum data values in a two-dimensional areasurrounding the current pixel location. These results 52 are sent to amodule 48 which also accepts as input the filtered frequency detectionvalues 46 and boosts the level of the frequency detection values basedon the pixel range and maximum values 52. The changes made to thefrequency detection values are based on threshold parameters which arecompared to the pixel data maximum and range values, as follows in TableThree:

TABLE THREE IF (Range < RangeThreshold1) AND (Max < MaxThreshold1) THENmultiply FrequencyDetectionValue by ScaleFactor1 ELSE IF (Range <RangeThreshold2) AND (Max < MaxThreshold2) THEN multiplyFrequencyDetectionValue by ScaleFactor2 ELSE IF (Range <RangeThreshold3) AND (Max < MaxThreshold3) THEN multiplyFrequencyDetectionValue by ScaleFactor3This has the result of boosting the frequency detection values in areasof low overall intensity or dynamic range. In the preferred embodiment,the following default values, in a Table Four, are used for thethresholds and multipliers:

TABLE FOUR RangeThreshold1 = 32 MaxThreshold1 = 96 ScaleFactor1 = 4RangeThreshold2 = 64 MaxThreshold2 = 128 ScaleFactor2 = 3RangeThreshold3 = 96 MaxThreshold3 = 192 ScaleFactor3 = 2These values can be programmed, however, and varied as needed on anapplication by application basis.

It will therefore be appreciated that a method for detecting interlacemotion artifacts includes detecting a presence of multiple verticalfrequencies in an image, analyzing relative levels of the presence ofmultiple vertical frequencies and deriving an indication of a presenceof motion artifacts. Also included is determining an overall measure ofimage intensity and dynamic range. The indication of the presence ofmotion artifacts is compensated in areas of low luminosity.

Also, it will be appreciated that a method for boosting frequencydetection values in areas of low brightness and contrast includesobtaining a plurality of input pixel data values, determining a maximumvalue, determining a range value and selectively boosting a frequencydetection value based upon the maximum value, the range value and aplurality of filtered frequency detection values. The selective boostingof a frequency detection value includes comparing the range value to afirst range threshold, comparing the maximum value to a first maximumthreshold, multiplying the frequency detection value by a first scalefactor if the range value is less than the first range threshold and themaximum value is less than the first maximum threshold and taking nofurther action if the range value is less than the first range thresholdand the maximum value is less than the first maximum threshold.

The method also includes comparing the range value to a second rangethreshold, comparing the maximum value to a second maximum threshold,multiplying the frequency detection value by a second scale factor ifthe range value is less than the second range threshold and the maximumvalue is less than the second maximum threshold and taking no furtheraction if the range value is less than the second range threshold andthe maximum value is less than the second maximum threshold. Alsoincluded is comparing the range value to a third range threshold,comparing the maximum value to a third maximum threshold, multiplyingthe frequency detection value by a third scale factor if the range valueis less than the third range threshold and the maximum value is lessthan the third maximum threshold and taking no further action if therange value is less than the third range threshold and the maximum valueis less than the third maximum threshold.

The level-boosted four-point f_(max) frequency detection value 54 andlevel-boosted eight-point f_(max) frequency detection value 56 are thencombined in an averaging module 58 which computes the numeric average 60of the two values. As noted above, the combination of the four-point andeight-point frequency detection values provides a more regular andconsistent response across a variety of video program material.

When the lower frequency detection values are very strong compared tothe f_(max) detection, it is likely that a true interlace motionartifact is not present. To correct this, the composite f_(max)frequency detection value 60 is sent to module 66 along with thelevel-boosted f_(max)/2 frequency detection value 62 and f_(max)/4 value64. These values are compared to certain threshold parameters, and amultiple of the low frequency detection values is subtracted from thef_(max) frequency detection value. In this manner, a strong detection ofeither or both of the lower frequencies causes the f_(max) frequencydetection value to be reduced in level, possibly to zero. A weakerdetection of the lower frequencies will still reduce the level of thef_(max) detection, but not to as great a degree, and will only reduce itto zero if the f_(max) detection itself is very weak. The threshold andlevel modification logic is as follows in Table Five:

TABLE FIVE IF (f_(max) < LowFreqThreshold1) THEN subtractLowFreqScaleFactor1* f_(max)/2 from f_(max) ELSE subtractLowFreqScaleFactor2* f_(max)/2 from f_(max) IF (f_(max)/4 <LowFreqThreshold2) THEN subtract LowFreqScaleFactor3* f_(max)/4 fromf_(max) ELSE subtract LowFreqScaleFactor4* f_(max)/4 from f_(max) IF(f_(max) < 0) THEN set f_(max) = 0The final comparison to zero is necessary since the f_(max) value may benegative after the two subtractions. In the preferred embodiment, thefollowing default values, of Table Six, are used for the thresholds andmultipliers:

TABLE SIX LowFreqThreshold1 = 32 LowFreqScaleFactor1 = 8LowFreqScaleFactor2 = 4 LowFreqThreshold2 = 200 LowFreqScaleFactor3 = 32LowFreqScaleFactor4 = 24These values can be programmed, however, and varied as needed on anapplication by application basis.

The level-corrected f_(max) frequency detection value 68 is thenfiltered by module 70 which computes a center-weighted horizontalaverage frequency detection value 72. This has the effect of smoothlychanging the frequency detection value near the boundaries of an area ofinterlace motion artifacts. A smooth, gradual change in the detectionvalue is necessary to prevent a noticeable, abrupt change in the way newpixels are calculated. The weighted average is computed as follows inEquation 3:HorWtdAvg=(F _(n−2)+2*F _(n−1)+8*F _(n)+2*F _(n+1) +F_(n+2))/8  Equation 3where F_(n) is the current input frequency detection value to thecenter-weighted filter, F_(n−1) is the previous input frequencydetection value, etc.

It will therefore be appreciated that a method for the prevention offalse detection of interlace motion artifacts includes obtaining aplurality of f_(max) frequency detection values; comparing the pluralityof f_(max) frequency detection values to a threshold and adjusting theplurality of f_(max) frequency detection values based upon thecomparison. The plurality of f_(max) frequency detection values includesa composite f_(max) frequency detection value, a level-boosted f_(max)/2frequency detection value and a level-boosted f_(max)/4 frequencydetection value.

The composite f_(max) frequency detection value is adjusted by comparingthe composite f_(max) frequency detection value to a first low frequencythreshold multiplying a first low frequency scale factor by thelevel-boosted f_(max)/2 frequency detection value and subtracting fromthe composite f_(max) frequency detection value if the composite f_(max)frequency detection value is less than the first low frequency thresholdand multiplying a second low frequency scale factor by the level-boostedf_(max)/2 frequency detection value and subtracting from the compositef_(max) frequency detection value if the composite f_(max) frequencydetection value is greater than the first low frequency threshold.

The composite f_(max) frequency detection value is also adjusted bycomparing the level-boosted f_(max)/4 frequency detection value to asecond low frequency threshold multiplying a third low frequency scalefactor by the level-boosted f_(max)/4 frequency detection value andsubtracting from the composite f_(max) frequency detection value if thelevel-boosted f_(max)/4 frequency detection value is less than thesecond low frequency threshold and multiplying a fourth low frequencyscale factor by the level-boosted f_(max)/4 frequency detection valueand subtracting from the composite f_(max) frequency detection value ifthe level-boosted f_(max)/4 frequency detection value is greater thanthe second low frequency threshold. The composite f_(max) frequencydetection value is set to zero if the composite f_(max) frequencydetection value is less than zero.

The composite f_(max) frequency detection value is lowpass filtered. Thelowpass filtering is achieved by obtaining a first and second previousf_(max) values, the composite f_(max) frequency detection value and anext and second next f_(max) values, doubling the first previous, andnext f_(max) values, octupling the composite f_(max) frequency detectionvalue, summing the doubled first previous f_(max) value, the doublednext f_(max) value, the octupled f_(max) frequency detection value withthe second previous and second next f_(max) value and dividing the sumby 8.

Finally, the filtered f_(max) frequency detection value 72 isthresholded at programmable upper and lower limits. The thresholding act74 is shown in greater detail as a graph in FIG. 4. Each pre-thresholdedfrequency detection value 72 is a number in the range zero to one. Thepost-thresholded values 76 also range from zero to one. The thresholdingact sets all values below a lower threshold 80 to zero, and all valuesabove an upper threshold 82 to one. Values between the upper and lowerthresholds are expanded to fill the range zero to one. Thresholding canalso be described by the following Equation 4:TFD=(PTFD−LowThreshold)/UpperThreshold  Equation 4where TFD is the thresholded frequency detection value 76, PTFD is thepre-thresholded frequency detection value 72, LowThreshold is the lowerthreshold 80, and UpperThreshold is the upper threshold 82. If theresult of the threshold calculation is greater than one, the result isset to one; if the result is less than zero, the result is set to zero.

While the forgoing process has been described with respect to use of theluminance values of the video data, the same technique can be utilizedwith chroma data. This allows the present invention to detect thepresence of interlace motion artifacts which are caused by chroma-onlymotion (i.e., where the luma level is constant but the chroma levelschange).

It will therefore be appreciated that the frequency-based interlacemotion artifact detection process of the present invention provides forimproved image quality and the reduction of the presence of interlacemotion artifacts. This is accomplished by a more accurate identificationof the presence of interlace motion artifacts with fewer erroneousdetections. The detection of multiple vertical frequencies along withlevel adjustments in areas of low brightness or contrast significantlyimprove the accuracy of the frequency detection process. The combinationof these techniques provides a low artifact, high-resolutiondeinterlaced image.

It will also be appreciated that a system for the reduction of interlacemotion artifacts by vertical frequency analysis includes a four-pointpartial discrete fourier transform module responsive to a set of fourvertically aligned luma data sample inputs selected from andapproximately centered about a set of eight vertically aligned luma datasample inputs and operative to develop a first frequency detectionvalue. Also included is an eight-point partial discrete fouriertransform module responsive to the set of eight vertically aligned lumadata sample inputs and operative to develop a second, third and fourthfrequency detection value. A dynamic range/maximum detection moduleresponsive to the set of eight vertically aligned luma data sampleinputs in conjunction with pixel data from a two-dimensional arraysurrounding a current input pixel and operative to develop a maximumdata value and a range value. The horizontal lowpass filter module isresponsive to the first, second, third and fourth frequency detectionvalues and operative to develop filtered first, second, third and fourthfrequency detection values. The detection value boost module isresponsive to the filtered first, second, third and fourth frequencydetection values, the maximum data value and the range value, and isoperative to develop a level boosted four-point f_(max) frequencydetection value, a level boosted eight-point f_(max) frequency detectionvalue, a level boosted f_(max)/2 frequency detection value and a levelboosted f_(max)/4 frequency detection value. An averaging module isresponsive to the level boosted four-point frequency detection value andthe level boosted eight-point frequency detection value, and isoperative to develop a numeric average. A threshold comparison/levelcorrection module is responsive to the numeric average, the levelboosted f_(max)/2 frequency detection value and the level boostedf_(max)/4 frequency detection value, and is operative to develop alevel-corrected f_(max) frequency detection value. The horizontalweighted average module is responsive to the level-corrected f_(max)frequency detection value and operative to develop a center-weightedhorizontal frequency detection value. Finally, a threshold adjust moduleis responsive to the center-weighted horizontal frequency detectionvalue and operative to develop a final frequency detection value.

While this invention has been described in terms of several preferredembodiments, it will be appreciated that those skilled in the art, uponreading the preceding specifications and studying the drawings, willrealize various alterations, additions, permutations, and equivalents asfall within the true spirit and scope of the invention.

1. A system for the reduction of interlace motion artifacts by verticalfrequency analysis comprising: a) a four-point partial discrete fouriertransform module responsive to a set of four vertically aligned luma orchroma data sample inputs selected from and approximately centered abouta set of eight vertically aligned luma or chroma data sample inputs andoperative to develop a first frequency detection value; b) aneight-point partial discrete fourier transform module responsive to theset of eight vertically aligned luma or chroma data sample inputs andoperative to develop a second, third and fourth frequency detectionvalue; c) a dynamic range/maximum detection module responsive to the setof eight vertically aligned luma or chroma data sample inputs inconjunction with pixel data from a two-dimensional array surrounding acurrent input pixel and operative to develop a maximum data value and arange value; d) a horizontal lowpass filter module responsive to thefirst, second, third and fourth frequency detection values and operativeto develop filtered first, second, third and fourth frequency detectionvalues; e) a detection value boost module responsive to the filteredfirst, second, third and fourth frequency detection values, the maximumdata value and the range value, operative to develop a level boostedfour-point f_(max) frequency detection value, a level boostedeight-point f_(max) frequency detection value, a level boosted f_(max)/2frequency detection value and a level boosted f_(max)/4 frequencydetection value; f) an averaging module responsive to the level boostedfour-point frequency detection value and the level boosted eight-pointfrequency detection value, operative to develop a numeric average; g) athreshold comparison/level correction module responsive to the numericaverage, the level boosted f_(max)/2 frequency detection value and thelevel boosted f_(max)/4 frequency detection value, operative to developa level-corrected f_(max) frequency detection value; h) a horizontalweighted average module responsive to the level-corrected f_(max)frequency detection value and operative to develop a center-weighted,horizontal frequency detection value; and i) a threshold adjust moduleresponsive to the center-weighted horizontal frequency detection valueand operative to develop a final frequency detection value.
 2. A systemas in claim 1, wherein the luma or chroma data is luma data.
 3. A systemas in claim 1, wherein the luma or chroma data is chroma data.
 4. Asystem as in claim 1, wherein the luma or chroma data comprises lumadata and chroma data.
 5. A method for the reduction of interlace motionartifacts by vertical frequency analysis, the method comprising: a)performing a four-point partial discrete Fourier transform responsive toa set of four vertically aligned luma or chroma data sample inputsselected from and approximately centered about a set of eight verticallyaligned luma data sample inputs and generating a first frequencydetection value; b) performing an eight-point partial discrete Fouriertransform responsive to the set of eight vertically aligned luma orchroma data sample inputs and generating a second, third, and fourthfrequency detection value; c) performing a dynamic range/maximumdetection operation responsive to the set of eight vertically alignedluma or chroma data sample inputs in conjunction with pixel data from atwo-dimensional array surrounding a current input pixel and generating amaximum data value and a range value; d) performing a horizontallow-pass filter operation responsive to the first, second, third, andfourth frequency detection values and generating filtered first, second,third, and fourth frequency detection values; e) performing a detectionvalue boost operation responsive to the filtered first, second, third,and fourth frequency detection values, the maximum data value and therange value, and generating a level boosted four-point f_(max) frequencydetection value, a level boosted eight-point f_(max) frequency detectionvalue, a level boosted f_(max)/2 frequency detection value, and a levelboosted f_(max)/4 frequency detection value; f) performing an averagingoperation responsive to the level boosted four-point frequency detectionvalue and the level boosted eight-point frequency detection value, andgenerating a numeric average; g) performing a threshold comparison/levelcorrection operation responsive to the numeric average, the levelboosted f_(max)/2 frequency detection value, and the level boostedf_(max)/4 frequency detection value, and generating a level-correctedf_(max) frequency detection value; h) performing a horizontal weightedaverage operation responsive to the level-corrected f_(max) frequencydetection value and generating a center-weighted, horizontal frequencydetection value; and i) performing a threshold adjust operationresponsive to the center-weighted horizontal frequency detection valueand generating a final frequency detection value.
 6. A method as inclaim 5, wherein the luma or chroma data is luma data.
 7. A method as inclaim 5, wherein the luma or chroma data is chroma data.
 8. A method asin claim 5, wherein the luma or chroma data comprises luma data andchroma data.
 9. A system for the reduction of interlace motion artifactscomprising: a) a partial discrete Fourier transform module responsive toa set of vertically aligned luma or chroma data sample inputs selectedfrom and approximately centered about a set of vertically aligned lumaor chroma data sample inputs and operative to develop a first frequencydetection value; b) a partial discrete Fourier transform moduleresponsive to the set of vertically aligned luma or chroma data sampleinputs and operative to develop a plurality of additional frequencydetection values; c) a dynamic range/maximum detection module responsiveto the set of vertically aligned luma or chroma data sample inputs inconjunction with pixel data from a two-dimensional array surrounding acurrent input pixel and operative to develop a maximum data value and arange value; d) a horizontal lowpass filter module responsive to thefrequency detection values and operative to develop filtered frequencydetection values; e) a detection value boost module responsive to thefiltered frequency detection values, the maximum data value and therange value, operative to develop a plurality of level boosted frequencydetection values; f) an averaging module responsive to the level boostedfrequency detection values, operative to develop a numeric average; g) athreshold comparison/level correction module responsive to the numericaverage, at to at least one of the level boosted frequency detectionvalues operative to develop a level-corrected frequency detection value;h) a horizontal weighted average module responsive to thelevel-corrected frequency detection value and operative to develop acenter-weighted, horizontal frequency detection value; and i) athreshold adjust module responsive to the center-weighted horizontalfrequency detection value and operative to develop a final frequencydetection value.
 10. A method for the reduction of interlace motionartifacts comprising: a) performing a partial discrete Fourier transformresponsive to a set of vertically aligned luma or chroma data sampleinputs selected from and approximately centered about a set ofvertically aligned luma or chroma data sample inputs and generating afirst frequency detection value; b) performing a partial discreteFourier transform operation responsive to the set of vertically alignedluma or chroma data sample inputs and generating a plurality ofadditional frequency detection values; c) performing a dynamicrange/maximum detection operation responsive to the set of verticallyaligned luma or chroma data sample inputs in conjunction with pixel datafrom a two-dimensional array surrounding a current input pixel andgenerating a maximum data value and a range value; d) performing ahorizontal low-pass filter operation responsive to the frequencydetection values and generating filtered frequency detection values; e)performing a detection value boost operation responsive to the filteredfrequency detection values, the maximum data value and the range value,generating a plurality of level boosted frequency detection values; f)performing an averaging operation responsive to the level boostedfrequency detection values, operative to develop a numeric average; g)performing a threshold comparison/level correction operation responsiveto the numeric average, at to at least one of the level boostedfrequency detection values generating a level-corrected frequencydetection value; h) performing a horizontal weighted average operationresponsive to the level-corrected frequency detection value andgenerating a center-weighted, horizontal frequency detection value; andi) performing a threshold adjust operation responsive to thecenter-weighted horizontal frequency detection value and generating afinal frequency detection value.
 11. A method as in claim 10, whereinthe luma or chroma data is luma data.
 12. A method as in claim 10,wherein the luma or chroma data is chroma data.
 13. A method as in claim10, wherein the luma or chroma data comprises luma data and chroma data.14. A Fourier transform unit comprising: a four-point partial discreteFourier transform module; and an eight-point partial discrete Fouriertransform module; the four-point partial discrete Fourier transformmodule being responsive to a set of vertically aligned luma or chromadata sample inputs selected from and approximately centered about a setof vertically aligned luma or chroma data sample inputs and operative todevelop a first frequency detection value; and the eight-point partialdiscrete Fourier transform module being responsive to the set of eightvertically aligned luma or chroma data sample inputs and operative todevelop at least one frequency detection value.
 15. The Fouriertransform unit in claim 14, wherein: the four-point partial discreteFourier transform module being responsive to a set of four verticallyaligned luma or chroma data sample inputs selected from andapproximately centered about a set of eight vertically aligned luma orchroma data sample inputs and operative to develop a first frequencydetection value; and the eight-point partial discrete Fourier transformmodule being responsive to the set of eight vertically aligned luma orchroma data sample inputs and operative to develop a second, third andfourth frequency detection value.
 16. The Fourier transform unit inclaim 15, further comprising: a dynamic range/maximum detection moduleresponsive to the set of eight vertically aligned luma or chroma datasample inputs in conjunction with pixel data from a two-dimensionalarray surrounding a current input pixel and operative to develop amaximum data value and a range value; a horizontal lowpass filter moduleresponsive to the first, second, third and fourth frequency detectionvalues and operative to develop filtered first, second, third and fourthfrequency detection values; and a detection value boost moduleresponsive to the filtered first, second, third and fourth frequencydetection values, the maximum data value and the range value, operativeto develop a level boosted four-point f_(max) frequency detection value,a level boosted eight-point f_(max) frequency detection value, a levelboosted f_(max)/2 frequency detection value and a level boostedf_(max)/4 frequency detection value.